Born Copenhagen, Denmark, October 12th 1990
Adress Fredericiagade 21D, st., 1310 Copenhagen K
Email magnusbitsch@gmail.com
Website LinkedIn
Phone +45 26 30 48 94
A degree in mathematical modelling and computation as an engineer combined with work experience in Data Science both internal and as a consultant has provided me with the skill set to model any data you throw at me through a wide variety of mathematical and statistical tools which I always seek to improve.
Playing american football at the top level in Denmark as a captain of the Copenhagen Towers and the Danish National Team has embraced my natural leadership abilities and taught me how to be a team player.
| - Statistical Modelling | - Azure | - Natural Leader - Team Captain |
| - Time Series Analysis | - Deep Learning | - Communication to non-mathematicians |
| - Machine Learning | - Reinforcement Learning | - Self-motivated |
| - Data Mining | - Problem Solving | - Keen to learn and improve skills |
2014 - 2016 The Technical University of Denmark,
Lyngby
GPA: 11.3 - Master (MSc) / Civilingeniør, cand. polyt.
Focus areas: Industrial and applied statistics, and
Stochastic dynamical modelling
Thesis: Statistical Learning for Energy Informatics (Grade: 12
(A))
Description: Applied mathematics and mathematical modelling as
well as use of modern computer equipment and analysis of large data
volumes. A Strong foundation in industrial statistics techniques such as
design of experiments, statistical process control, process capability
analysis, reliability analysis, etc. Tools in analyzing and modelling
dynamical systems based on available time series of data which can be
applied within important areas like finance, pharmaceutics, biology, and
energy production (wind, solar, ..).
Link: Mathematical
Modelling and Computation
2010 - 2014 The Technical University of Denmark,
Lyngby
GPA: 7.9 - Bachelor (BEng and BSc)
Description: Sound mathematical foundations and experience
in developing and running mathematical models in different fields.
Link: Mathematical
Modelling and Computation
Fall 2012 Oregon State University, Oregon,
USA
Description: Exchange through DTU.
2006 – 2010 HTX Sukkertoppen, Valby
Description: High School (Gymnasium).
2007/2008 Waynesfield Goshen High School, Ohio,
USA
Description: High School, 11th grade ”Junior year”. Exchange through YFU.
2022 - Kapacity A/S, Copenhagen
Area: Kapacity AI
Description: Working with predictive modelling, statistics,
data mining, machine learning and deep learning primarily using the
Azure cloud platform. Framework for comparing and selecting output from
competing models in production. Primary areas: Churn, cross-sales,
CLV.
Converting Machine Learning and advanced statistical analysis into
concrete data products targeted at various businesses.
A Senior Data Science Architect has several years of experience
deploying Data Science models in production in customer environments,
both on premise and Azure cloud. The have broad and deep experience with
Data Science methods, tools and algorithms and know how to deploy each
of these models to production. They can facilitate a business discussion
and design the data science architecture to match customers’
requirements to data environment.
The profile secures that team members and colleagues are up to date on
Kapacitys Best Practice for implementing. Data Science methods, based on
i.e infrastructure-as-code, CI/CD pipelines, DevOps methods, Docker
containers and virtual analysis environments. Link: Kapacity
2019 - 2022 Kapacity A/S,
Copenhagen
Area: Kapacity AI
Description: Senior data scientist in BI consultancy. Working
with predictive modelling, statistics, data mining, machine learning and
deep learning primarily using the Azure cloud platform. Framework for
comparing and selecting output from competing models in production.
Primary areas: Churn, cross-sales, CLV.
Converting Machine Learning and advanced statistical analysis into
concrete data products targeted at various businesses.
A Senior Data Science Architect has several years of experience in
putting Data Science models into production on the customer’s
environment, whether on-premise or Azure cloud. They have a broad
understanding of Data Science methods, tools and algorithms and know
processes with production setting of models within each. They know how
to drive the business dialogue and to adapt the setup of the data
science architecture to the customer’s other wishes for the data
environment.
The profile actively works to ensure that employees and colleagues seek
knowledge and sparring relationships regarding Kapacity’s Best Practice
implementation within Data Science methods, which are based on the use
of infrastructure-as-code, CI/CD pipelines, DevOps methods, Docker
containers and virtual analysis environments.
Link: Kapacity
2019 - 2019 Nuuday (TDC Group),
Copenhagen
Area: Commercial Data Science
Description: Chapter lead and senior data scientist supervising
8 data scientist and collaborating with stakeholders. Working with
predictive modelling, statistics, data mining, machine learning and deep
learning. Framework for comparing and selecting output from competing
models in production. Primary areas: Churn, cross-sales, CLV,
maintaining models in production.
Reference: Jonas Munk | jmu@nuuday.dk
Link: TDC Group
2016 - 2019 TDC Group, Copenhagen
Area: AI & Robotics
Description: Working with predictive modelling, statistics,
data mining, machine learning and deep learning. Framework for comparing
and selecting output from competing models in production. Primary areas:
Churn, cross-sales, CLV, invoice classification, maintaining models in
production, supervising junior data scientists and collaborating with
stakeholders.
Reference: Jonas Munk | jmu@nuuday.dk
Link: TDC Group
2015 – 2016 The Technical University of Denmark,
Lyngby
Area: DTU Statistical Consulting Center
Description: Developing statistical reports for internally and
externally use in collaboration with professors in the Department of
Applied Mathematics and Computer Science.
Reference: Bjarne Kjær Ersbøll | bker@dtu.dk
2013 – 2015 MEGAFON, Frederiksberg
Area: Data
Description: In the department of data I set up of
questionnaires for online or phone interviews. Furthermore, I tested
ongoing questionnaires and created reports based on completed
questionnaires. Smaller tasks included maintaining databases, weighting
of questionnaire answers and overseeing the completion of
questionnaires.
Reference: Ulrik S. Nielsen | usn@megafon.dk
Link: MEGAFON
2011 – 2014 KEA, Copenhagen
Area: Københavns Erhvervs Akademi
Description: Three semesters of teaching 1st year math for
electricians who studied to become qualified electricians.
Python, R, R-Sweave, Docker, Azure, Azure DevOps Pipelines
SQL, Databricks, Git, Bash, Markdown, MLOps, LATEX
Matlab, SAS, Java, C
2019 A markov-switching model for building occupant
activity estimation.
Wolf, S., Møller, J. K., Bitsch, M. A., Krogstie, J., & Madsen, H. (2019). A Markov-Switching model for building occupant activity estimation. Energy and Buildings, 183, 672-683. https://doi.org/10.1016/j.enbuild.2018.11.041
2016
Symptoms and quality of life in patients with chronic obstructive pulmonary disease treated with aclidinium in a real-life setting.
Lange, Peter & Godtfredsen, Nina & Olejnicka, Beata & Paradis, Bo-Anders & Curiac, Dan & Humerfelt, Sjur & Telg, Gunilla & Christensen, Helene & Bitsch, Magnus & Andersen, Elisabeth & Bjermer, Leif. (2016). Symptoms and quality of life in patients with chronic obstructive pulmonary disease treated with aclidinium in a real-life setting. European Clinical Respiratory Journal. 3. 10.3402/ecrj.v3.31232.
Fall 2012 Oregon State University
2007/2008 Waynesfield Goshen High School (Jr/11th
grade), Ohio, USA
Danish: Mothertongue
English: Full professional proficiency
Deutsch: Basic (simple words and phrases only)
American football | Sports in general | Challenges
2012 - Team Captain
2022 National Champion
2021 National Champion
2019 National Champion (2nd)
2018 National Champion
2017 National Champion, Most Valuable Player (Team),
Most Valuable Player (Mermaid Bowl - National Championship)
2016 National Champion (2nd)
2014 National Champion, Best Defensive Player (Team)
2013 National Champion, Most Valuable Player (Team)
2011 Best Defensive Player (Team)
2016 - Team Captain
2018 European Championship (6th)
2014 European Championship (6th)
2013 · European Championship (1st) (B-group)